382 citations · 801 across the 48 of their papers we have counts for
3 papers · 1 filter
Guided Deep Reinforcement Learning for Swarm Systems
Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann
In this paper, we investigate how to learn to control a group of cooperative agents with limited sensing capabilities such as robot swarms. The agents have only very basic sensor c…
Local Communication Protocols for Learning Complex Swarm Behaviors with Deep Reinforcement Learning
Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann
Swarm systems constitute a challenging problem for reinforcement learning (RL) as the algorithm needs to learn decentralized control policies that can cope with limited local sensi…
Hybrid control trajectory optimization under uncertainty
Joni Pajarinen, Ville Kyrki, Michael Koval +3
Trajectory optimization is a fundamental problem in robotics. While optimization of continuous control trajectories is well developed, many applications require both discrete and c…